Due to advances in computing technology, businesses today are able to operate more efficiently when compared to substantially similar businesses only a few years ago. For example, internal networking enables employees of a company to communicate instantaneously by email, quickly transfer data files to disparate employees, manipulate data files, share data relevant to a project to reduce duplications in work product, etc. Furthermore, advancements in technology have enabled factory applications to become partially or completely automated. For instance, operations that once required workers to put themselves proximate to heavy machinery and other various hazardous conditions can now be completed at a safe distance therefrom.
Further, imperfections associated with human action have been minimized through employment of highly precise machines. Many of these factory devices supply data related to manufacturing to databases that are accessible by system/process/project managers on a factory floor. For instance, sensors and associated software can detect a number of instances that a particular machine has completed an operation given a defined amount of time. Also, data from sensors can be delivered to a processing unit relating to system alarms. Thus, a factory automation system can review collected data and automatically and/or semi-automatically schedule maintenance of a device, replacement of a device, and other various procedures that relate to automating a process.
While various advancements have been made with respect to automating an industrial process, utilization and design of controllers has been largely unchanged. In more detail, industrial controllers have been designed to efficiently undertake real-time control. For instance, conventional industrial controllers receive data from sensors and, based upon the received data, control an actuator, drive, or the like. These controllers recognize a source and/or destination of the data by way of a symbol and/or address associated with the source and/or destination. More particularly, industrial controllers include communications ports and/or adaptors, and sensors, actuators, drives, and the like are communicatively coupled to such ports/adaptors. Thus, a controller can recognize device identify when data is received and further deliver control data to an appropriate device.
As can be discerned from the above, data associated with conventional industrial controllers is created, delivered, and/or stored with a flat namespace data structure. In other words, all that can be discerned by reviewing data received and/or output by a controller is an identity of an actuator or sensor and a status thereof. This industrial controller architecture operates efficiently for real-time control of a particular device—however, problems can arise when data from industrial controllers is desired for use by a higher-level system. For example, if data from the controller was desired for use by a scheduling application, individual(s) familiar with the controller must determine which data is desirable, sort the data, package the data in a desired format, and thereafter map such data to the scheduling application. This introduces another layer of software, and thus provides opportunities for confusion in an industrial automation environment. The problem is compounded if several applications wish to utilize similar data. In operation, various controllers output data, package it in a flat namespace structure, and provide it to a network. Each application utilizing the data copies such data to internal memory, sorts the data, organizes the data, and packages the data in a desired format. Accordingly, multiple copies of similar data exist in a plurality of locations, where each copy of the data may be organized and packaged disparately.
Moreover, due to the aforementioned deficiencies associated with conventional controllers, it is currently not possible to provide detailed information to a controller regarding lifecycle and/or deployment of data. Rather, data generated by the controller is provided to a network, and then the data is consumed by applications that may utilize such data. The applications then peruse the data and have software associated therewith that is utilized to determine whether such data is needed, what the lifecycle is with respect to the data, and the like. This determination is made with respect to each application, thus creating inefficiency and affecting network speed.